A neural network-based model for assessing 3D printable concrete performance in robotic fabrication

Weijiu Cui, Dongsheng Ji, Liang Shen, Shiyong Su, Xinyu Shi, Jidong Liu, Zirui Bai, Yubo Sun, Jian Gong and Yaxin Tao

Results in Engineering, 2025, 27, 105970
DOI: 10.1016/j.rineng.2025.105970

Characterisation of a 3D-printed alkali-activated material based on waste mineral wool at room and elevated temperatures

Majda Pavlin, Barbara Horvat, Romana Cerc Korošec, Rok Capuder, Lidija Korat and Vilma Ducman

Cement and Concrete Composites, 2024, 147, 105445
DOI: 10.1016/j.cemconcomp.2024.105445

Machine learning and sustainable geopolymer materials: A systematic review

Ho Anh Thu Nguyen, Duy Hoang Pham, Yonghan Ahn, Bee Lan Oo and Benson Teck Heng Lim

Materials Today Sustainability, 2025, 30, 101095
DOI: 10.1016/j.mtsust.2025.101095

Unraveling the hardening mechanism during laser-induced slip casting of lithium aluminate-microsilica slurry

Sebastian Simon and Gregor J.G. Gluth

Open Ceramics, 2021, 5, 100060
DOI: 10.1016/j.oceram.2021.100060

Possibilities of Checking Water Content in Porous Geopolymer Materials Using Impedance Spectroscopy Methods

Dariusz Mierzwiński, Janusz Walter and Dominika Wanat

Materials, 2023, 16, 5190
DOI: 10.3390/ma16145190

Additive manufacturing of geopolymer composites for sustainable construction: critical factors, advancements, challenges, and future directions

R. S. Krishna, Asif Ur Rehman, Jyotirmoy Mishra, Suman Saha, Kinga Korniejenko, Rashid Ur Rehman, Metin Uymaz Salamci, Vincenzo M. Sglavo, Faiz Uddin Ahmed Shaikh and Tanvir S. Qureshi

Prog Addit Manuf, 2025, 10, 1003
DOI: 10.1007/s40964-024-00703-z

Data-driven analysis in 3D concrete printing: predicting and optimizing construction mixtures

Rodrigo Teixeira Schossler, Shafi Ullah, Zaid Alajlan and Xiong Yu

AI Civ. Eng., 2025, 4
DOI: 10.1007/s43503-024-00044-4

Sustainable Polymer Composites Manufacturing through 3D Printing Technologies by Using Recycled Polymer and Filler

Daniela Fico, Daniela Rizzo, Valentina De Carolis, Francesco Montagna and Carola Esposito Corcione

Polymers, 2022, 14, 3756
DOI: 10.3390/polym14183756

Developing a novel strength predictive modeling for 3D printable geopolymer concrete: An interpretable data-driven approach

Md Nasir Uddin, Md Ibrahim Mostazid, Md Abdul Motaleb Faysal and Xijun Shi

Structures, 2025, 82, 110405
DOI: 10.1016/j.istruc.2025.110405

Optimizing rheological properties of 3D printed cementitious materials via ensemble machine learning

Muhammad Saeed Zafar, Farid Javadnejad and Maryam Hojati

Additive Manufacturing, 2025, 109, 104889
DOI: 10.1016/j.addma.2025.104889

Hybrid Materials Based on Fly Ash, Metakaolin, and Cement for 3D Printing

Joanna Marczyk, Celina Ziejewska, Szymon Gądek, Kinga Korniejenko, Michał Łach, Mateusz Góra, Izabela Kurek, Neslihan Doğan-Sağlamtimur, Marek Hebda and Magdalena Szechyńska-Hebda

Materials, 2021, 14, 6874
DOI: 10.3390/ma14226874

Alkali activated materials applied in 3D printing construction: A review

Maria Júlia Bassan de Moraes, Ester Yukimi Nagata, Afonso José Felício Peres Duran and João Adriano Rossignolo

Heliyon, 2024, 10, e26696
DOI: 10.1016/j.heliyon.2024.e26696

Research status and prospect of machine learning in construction 3D printing

Songyuan Geng, Qiling Luo, Kun Liu, Yunchao Li, Yuchen Hou and Wujian Long

Case Studies in Construction Materials, 2023, 18, e01952
DOI: 10.1016/j.cscm.2023.e01952

Progress and Opportunities for Machine Learning in Materials and Processes of Additive Manufacturing

Wei Long Ng, Guo Liang Goh, Guo Dong Goh, Jyi Sheuan Jason Ten and Wai Yee Yeong

Advanced Materials, 2024, 36
DOI: 10.1002/adma.202310006

Exploratory literature review and scientometric analysis of artificial intelligence applied to geopolymeric materials

Aldo Ribeiro de Carvalho, Romário Parreira Pita, Thaís Mayra de Oliveira, Guilherme Jorge Brigolini Silva and Julia Castro Mendes

Engineering Applications of Artificial Intelligence, 2025, 145, 110210
DOI: 10.1016/j.engappai.2025.110210

Analyzing the compressive strength of one-part geopolymers using experiment and machine learning approaches

Jingyu Wei, Keyu Chen, Hongchuan Yu, Shiqi Wang, Shuyang Zhang and Chonggen Pan

Journal of Building Engineering, 2024, 98, 111429
DOI: 10.1016/j.jobe.2024.111429

A novel compressive strength estimation approach for 3D printed fiber-reinforced concrete: integrating machine learning and gene expression programming

Md Nasir Uddin, Junhong Ye, M. Aminul Haque, Kequan Yu and Lingzhi Li

Multiscale and Multidiscip. Model. Exp. and Des., 2024, 7, 4889
DOI: 10.1007/s41939-024-00439-x

Machine Learning in Screening High Performance Electrocatalysts for CO2 Reduction

Ning Zhang, Baopeng Yang, Kang Liu, Hongmei Li, Gen Chen, Xiaoqing Qiu, Wenzhang Li, Junhua Hu, Junwei Fu, Yong Jiang, Min Liu and Jinhua Ye

Small Methods, 2021, 5
DOI: 10.1002/smtd.202100987

Geopolymer Concrete: A Material for Sustainable Development in Indian Construction Industries

Manvendra Verma, Nirendra Dev, Ibadur Rahman, Mayank Nigam, Mohd. Ahmed and Javed Mallick

Crystals, 2022, 12, 514
DOI: 10.3390/cryst12040514

Multi-objective adaptive experimental approach for optimizing 3D concrete printing mixtures and parameters incorporating construction and demolition waste for sustainable construction

Thomas Tawiah Baah, Hee-Jeong Kim and Marat I. Latypov

Discov. Concr. Cem., 2025, 1
DOI: 10.1007/s44416-025-00033-5

Machine Learning-Based Predictive Model for Tensile and Flexural Strength of 3D-Printed Concrete

Ammar Ali, Raja Dilawar Riaz, Umair Jalil Malik, Syed Baqar Abbas, Muhammad Usman, Mati Ullah Shah, In-Ho Kim, Asad Hanif and Muhammad Faizan

Materials, 2023, 16, 4149
DOI: 10.3390/ma16114149